Editorial Material
Neurosciences
Chie Satou, Rainer W. Friedrich
Summary: In their study, Gurnani and Silver found that activity across Golgi cells, a major type of inhibitory interneuron in the cerebellar cortex, is multidimensional and modulated by behavior, suggesting multiple functions for inhibition in cerebellar computations.
Article
Biology
Hunter E. Halverson, Jinsook Kim, Andrei Khilkevich, Michael D. Mauk, George J. Augustine, Upinder Singh Bhalla
Summary: The study demonstrates that the feedback inhibitory circuit between cerebellar Purkinje cells and molecular layer interneurons plays a crucial role in regulating neuronal activity during learning processes and learning-related movements.
Review
Neurosciences
Court Hull, Wade G. Regehr
Summary: The cerebellar cortex is a crucial system for neural circuitry and learning. Recent research has revealed the diverse neuron types, synaptic connections, and plasticity mechanisms within the cerebellar cortex. Despite the inability to construct a comprehensive model of cerebellar learning, the cerebellum remains an ideal system for studying the connection between neuronal function and behavior.
ANNUAL REVIEW OF NEUROSCIENCE
(2022)
Article
Automation & Control Systems
Jin-Yeol Yu, Jin-Young Kim, Seung-Min Song, Zacharie Ayubu, In-Dong Kim
Summary: This article proposes a new thyristor dc solid-state circuit breaker, which can naturally charge the commutation capacitor without complicated switching operation. It not only can perform the fast breaking of fault current, but also the operating duties of reclosing and rebreaking. The operating characteristics of the proposed dc SSCB are verified by the experimental results.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2021)
Article
Neurosciences
Jia Zhu, Hana Hasanbegovic, Liu D. Liu, Zhenyu Gao, Nuo Li
Summary: The study reveals the interaction between the neocortex and cerebellum and how they form functional networks to orchestrate motor planning. Hotspot regions with conjunctive input-output connectivity play a crucial role in maintaining preparatory activity and correct movement, while other cerebellar regions have little contribution.
NATURE NEUROSCIENCE
(2023)
Article
Biology
Marjorie Xie, Samuel P. Muscinelli, Kameron Decker Harris, Ashok Litwin-Kumar
Summary: This article discusses the neural representation models and learning theories of the cerebellar granule cell layer. The research findings suggest that for tasks involving continuous input-output transformations and smooth motor control, the optimal granule cell representation is denser than predicted by traditional theories.
Article
Chemistry, Physical
Alireza Ahmadianyazdi, Ngoc Hoang Lan Nguyen, Jie Xu, Vikas Berry
Summary: The sensitivity of graphene's Raman characteristics can be utilized for sensing applications. By recording the Raman spectroscopy of graphene in contact with a chemical/biological analyte, the correlation between analyte properties and graphene's electronic properties can be revealed. We demonstrate the principle and operation of glucose measurement using graphene's Raman spectroscopy, including both affinity and enzymatic detection methods.
Article
Engineering, Electrical & Electronic
Bo Wang, Jiapeng Hu, Wei Hua, Zheng Wang
Summary: This article analyzes the fault operation behavior of fault-tolerant machine drives, specifically focusing on a triple-redundant three-phase permanent magnet-assisted synchronous reluctance machine. The study explains the mutual-coupling mechanism of different three-phase modules through analyzing magnetomotive force distribution, revealing the presence of second harmonics in the dq-axis currents, voltages, and torque during fault conditions. The need for advanced control techniques to enhance current tracking capability in post-fault operation conditions is highlighted.
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION
(2021)
Article
Engineering, Electrical & Electronic
Qinghui Hong, Shen Man, Jingru Sun, Sichun Du, Jiliang Zhang
Summary: This paper proposes full hardware in-memory computing circuits based on programmable memristor unit array that can solve combinatorial matrix operations of any order in just one step. By introducing two basic circuit modules, matrix multiplication and matrix equation can be solved separately. Furthermore, these basic modules can be linked to solve combinatorial matrix operations with different forms. Each module can parallel program the value of each memristor in the memristor unit array and complete one-step computation by hardware.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS
(2023)
Article
Computer Science, Information Systems
Qingsen Wu, Haixu Liu, Jian Xin, Lin Li, Zuochang Ye, Yan Wang
Summary: In this paper, a multi-output deep neural network (DNN) structure is proposed to model the direct-current parameters of transistors and replace look-up tables (LUTs) in circuit design. The proposed DNN models significantly reduce storage space occupation and prediction time overhead compared to LUTs. Additionally, an automated circuit migration design method using DNN models in different technologies is introduced, which reduces time overhead by more than 40% compared to using LUTs.
Article
Chemistry, Physical
Barbara Scalvini, Vahid Sheikhhassani, Alireza Mashaghi
Summary: The relationship between the topology of a protein and its folding kinetics is explored in this study. Basic topological features can influence the folding rate and mechanistic insight into folding mechanisms can be inferred from topological parameters. The study introduces a new mathematical framework to define and extract the topology of native protein conformations.
PHYSICAL CHEMISTRY CHEMICAL PHYSICS
(2021)
Article
Engineering, Electrical & Electronic
Marco Crescentini, Sana Fatima Syeda, Gian Piero Gibiino
Summary: This tutorial provides a comprehensive insight into Hall-effect current sensors, covering their fundamental principles, design, implementation, and modeling methods. It is mainly aimed at students and non-expert readers, but also discusses specific design aspects and dispersion effects.
IEEE SENSORS JOURNAL
(2022)
Review
Chemistry, Multidisciplinary
Xiaosheng Zhang, Caoer Jia, Jinyu Zhang, Linlin Zhang, Xuying Liu
Summary: This article summarizes the working principles of smart responses, self-charging, electrochromic, and battery integration in zinc ion batteries (ZIBs), and prospects emerging strategies to address current challenges and the development of smart ZIB systems.
Article
Clinical Neurology
Anna Sadnicka, Lorenzo Rocchi, Anna Latorre, Elena Antelmi, James Teo, Isabel Parees, Britt S. Hoffland, Kristian Brock, Katja Kornysheva, Mark J. Edwards, Kailash P. Bhatia, John C. Rothwell
Summary: This study aimed to examine the influence of dystonia on eyeblink conditioning and explore its relationship with sex, age, and dystonia subtypes. The results showed that isolated dystonia and its subtypes had similar eyeblink conditioning levels compared to the control group, and a wide range of variability was observed in both healthy individuals and dystonia patients. This finding suggests that there is no global cerebellar learning deficit in isolated dystonia.
MOVEMENT DISORDERS
(2022)
Article
Neurosciences
Ted Maldonado, Trevor Bryan Jackson, Jessica A. Bernard
Summary: This study investigated the impact of transcranial direct current stimulation on cerebellar and cortical activation. The findings showed that anodal stimulation worsened task performance and increased cortical activation in parietal and frontal regions.
HUMAN BRAIN MAPPING
(2023)
Article
Neurosciences
Thomas R. Reppert, Ioannis Rigas, David T. Herzfeld, Ehsan Sedaghat-Nejad, Oleg Komogortsev, Reza Shadmehr
JOURNAL OF NEUROPHYSIOLOGY
(2018)
Article
Neurosciences
David J. Herzfeld, Yoshiko Kojima, Robijanto Soetedjo, Reza Shadmehr
NATURE NEUROSCIENCE
(2018)
Article
Neurosciences
Ehsan Sedaghat-Nejad, David J. Herzfeld, Reza Shadmehr
JOURNAL OF NEUROSCIENCE
(2019)
Article
Neurosciences
Ehsan Sedaghat-Nejad, David J. Herzfeld, Paul Hage, Kaveh Karbasi, Tara Palin, Xiaoqin Wang, Reza Shadmehr
JOURNAL OF NEUROPHYSIOLOGY
(2019)
Article
Neurosciences
Stuart Behling, Stephen G. Lisberger
JOURNAL OF NEUROPHYSIOLOGY
(2020)
Article
Biology
Timothy R. Darlington, Stephen G. Lisberger
Correction
Neurosciences
Chris I. De Zeeuw, Stephen G. Lisberger, Jennifer L. Raymond
NATURE NEUROSCIENCE
(2021)
Article
Neurosciences
Chris I. De Zeeuw, Stephen G. Lisberger, Jennifer L. Raymond
Summary: Recent research has revealed new connections between cerebellar neurons, abundant inputs related to reward, a cellular solution for the temporal credit assignment problem, and has restructured theories of cerebellar learning. The discoveries challenge historical views of the cerebellum as a simple sensorimotor controller and highlight its involvement in cognitive functions. The diversity and dynamism of the cerebellum provide a roadmap for future research and define major new research directions.
NATURE NEUROSCIENCE
(2021)
Article
Psychology, Biological
Scott T. Albert, Jihoon Jang, Hannah R. Sheahan, Lonneke Teunissen, Koenraad Vandevoorde, David J. Herzfeld, Reza Shadmehr
Summary: This study suggests that human motor adaptation has an upper limit linked to implicit learning. The sensitivity of the implicit learning system to errors decreases as perturbation variability increases, affecting the overall adaptation limit.
NATURE HUMAN BEHAVIOUR
(2021)
Article
Neurosciences
Nathan J. Hall, David J. Herzfeld, Stephen G. Lisberger
Summary: The research evaluates existing spike sorters and introduces a new method, FBP, that effectively addresses various sorting challenges. With multiple steps, FBP identifies unique neuron waveforms, optimally assigns spike events, resolves inaccuracies, and handles drifting neurons during recordings. By comparing with other sorters and examining performance on ground-truth data sets, the study reveals the tradeoff between speed, channels processed, and failure modes of spike sorting algorithms.
JOURNAL OF NEUROPHYSIOLOGY
(2021)
Article
Multidisciplinary Sciences
Seth W. Egger, Stephen G. Lisberger
Summary: The transformation of sensory input to motor output is often explained as a decoder operating on neural representations. In this study, the authors seek to understand sensory decoding by mimicking neural circuitry in the decoder's design. Their results show that changing the size of a target for smooth pursuit eye movements affects the relationship between variance and mean of the evoked behavior, contradicting traditional decoding approaches. They propose a circuit model for pursuit that includes multiple parallel pathways and variation sources, demonstrating the power of re-imagining decoding as processing through parallel pathways in neural systems.
NATURE COMMUNICATIONS
(2022)
Article
Neurosciences
Stuart Behling, Stephen G. Lisberger
Summary: Visual motion drives smooth pursuit eye movements through a sensory-motor decoder. Reduced dot coherence decreases the amplitude of MT population response during pursuit initiation without changing the preferred speed. The decoder that works for pursuit initiation fails to explain the paradox of steady-state eye speeds not accelerating to the target speed under low dot coherence.
JOURNAL OF NEUROPHYSIOLOGY
(2023)